Introduction to R

Jonathan Cornelissen

Co-founder and CEO of DataCamp

Jonathan Cornelissen is one of the co-founders of DataCamp, and is interested in everything related to data science, R, education and entrepreneurship. He holds a PhD in financial econometrics, and is the author of an R package for quantitative finance. DataCamp is the second education start-up he founded, and the first one that went international. In his spare time, he loves to do some programming, especially in Ruby on Rails.

Course Description

In this introduction to R, you will master the basics of this beautiful open source language, including factors, lists and data frames. With the knowledge gained in this course, you will be ready to undertake your first very own data analysis. With over 2 million users worldwide R is rapidly becoming the leading programming language in statistics and data science. Every year, the number of R users grows by 40% and an increasing number of organizations are using it in their day-to-day activities. Leverage the power of R by completing this free R online course today!

1

Intro to basics

In this chapter, you will take your first steps with R. You will learn how to use the console as a calculator and how to assign variables. You will also get to know the basic data types in R. Let's get started!

Vectors

In this free R course, we'll take you on a trip to Vegas, where you will learn how to analyze your gambling results using vectors in R! After completing this chapter, you will be able to create vectors in R, name them, select elements from them and compare different vectors.

Matrices

In this chapter you will learn how to work with matrices in R. By the end of the chapter, you will be able to create matrices and to understand how you can do basic computations with them. You will analyze the box office numbers of Star Wars to illustrate the use of matrices in R. May the force be with you!

Factors

Very often, data falls into a limited number of categories. For example, human hair color can be categorized as black/brown/blonde/red/grey/white (and perhaps a few more options for people who dye it). In R, categorical data is stored in factors. Given the importance of these factors in data analysis, you should start learning how to create, subset and compare them now!

Data frames

Most data sets you will be working with will be stored as data frames. By the end of this chapter focused on R basics, you will be able to create a data frame, select interesting parts of a data frame and order a data frame according to certain variables.

Resources

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About

DataCamp offers interactive R and Python courses on topics in data science, statistics, and machine learning. Learn from a team of expert teachers in the comfort of your browser with video lessons and fun coding challenges.